code: def _rwth_manual_metric(preds, targets) -> Tensor:
      """Baseline implementation of metric.
  
      The results were obtained w.r.t. the examples defined in `tests.text.inputs` with the script from
      https://github.com/rwth-i6/ExtendedEditDistance.
  
      """
      ans_1 = tensor(0.24248056001808083)
      ans_2 = tensor(0.19152276295133436)
  
      hypothesis = "It is a guide to action which ensures that the military always obeys the commands of the party"
  
      # If hypothesis A and B are in preds, the average of ans_1 and ans_2 is given
      if len(preds) == 4:
          return (ans_1 + ans_2) / 2
      # If only hypothesis A or B are given, ans_1 and ans_2 are given, respectively
      if hypothesis in preds:
          return ans_1
      return ans_2
  
file_path: torchmetrics/tests/unittests/text/test_eed.py
imports: from functools import partial
  import pytest
  from torch import Tensor, tensor
  from torchmetrics.functional.text.eed import extended_edit_distance
  from torchmetrics.text.eed import ExtendedEditDistance
  from unittests.text.helpers import TextTester
  from unittests.text.inputs import _inputs_single_reference, _inputs_single_sentence_multiple_references
label_desc: Use image node_id 1 for calling a global function with example usage: _rwth_manual_metric(preds, targets) and returns: ans_2, unknown, ans_1